• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1116-1123
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• 2015

The lifetime of a geostationary satellite depends on the residual propellant amount and therefore the precise residual propellant gauging is very important for the mitigation of economic loss arised from premature removal of satellite from its orbit, satellites replacement planning, slot management and so on. In this paper, the thermal mass method and its uncertainty are described. The residual propellant analysis of a geostationary satellite is simulated based on the KOREASAT data and the uncertainty of thermal mass method is calculated by using the Monte Carlo method. The results of this study show the importance parameter of estimation residual propellant using the thermal mass method.

• Journal of Industrial Technology
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• v.31 no.B
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• pp.107-112
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• 2011

Recently, climate change around the world due to global warming has became an important issue and damages by climate change have a bad effect on human life. Changes of Sea Surface Temperature(SST) is associated with natural disaster such as Typhoon and El Nino. So we predicted daily future SST using Statistical Downscaling Method and CGCM 3.1 A1B scenario. 9 points of around Korea peninsular were selected to predict future SST and built up a regression model using Multiple Linear Regression. CGCM 3.1 was simulated with regression model, and that comparing Probability Density Function, Box-Plot, and statistical data to evaluate suitability of regression models, it was validated that regression models were built up properly.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.267-270
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• 2009

최근 우리나라는 기후온난화 등으로 인해 봄철과 겨울철에 심각한 가뭄이 자주 발생하고 있으며 그 정도는 점차 심해지고 있다. 2001년과 2002년 사이에 발생한 가뭄으로 약 100여개 시군에서 제한급수가 시행되기도 하였으며 2008년 말부터 발생하고 있는 남부지방의 가뭄은 식수를 걱정해야 할 정도로 심각한 실정이다. 이러한 기후변화는 수돗물의 안정적인 공급을 위한 수자원확보를 어렵게 하고 있다. 특히 하천수를 취수원으로 하고 있는 지방상수도의 경우 수돗물의 안정적인 공급과 수질측면에서 가뭄에 매우 취약한 조건을 가지고 있다. 따라서 이러한 가뭄에 대처하고 안정적인 물 공급을 제공할 수 있는 광역상수도의 역할이 중요해 지고 있다. 광역상수도는 여름철 홍수기에 가두어 놓은 댐의 물을 사용함으로써 안정적으로 물을 제공할 수 있다. 광역상수도는 가뭄시 안정적인 수돗물을 공급할 수 있을 뿐만 아니라 지역간의 요금편차를 제거하여 수도요금의 지역간 형평성을 고려할 수 있다. 또한 광역상수도를 사용하는 지방자치단체의 경우, 지방상수원 보호구역의 해제로 인해 지역개발을 활성화 시킬 수 있으며 국가차원에서도 물관리의 효율성을 증대시킬 수 있다. 본 연구는 이러한 광역상수도의 사회적 편익을 조건부 가치측정법(CVM)을 이용하여 추정하였다. 조건부가치측정법은 비사장 재화에 대한 가치를 추정할 수 있는 통계적 방법이다. 추정결과 안정적인 물공급을 위한 광역상수도의 가치는 음의 효용을 허용하지 않았을 경우, 가구당 5,796원의 지불의사금액으로 추정되었다. 이러한 결과는 광역상수도의 투자계획시 정책자료로 사용될 수 있으며 물정책 당국자에게 물관리측면에서 유용한 자료로 사용될 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.57-63
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• 2008

In this paper, we present an efficient noise reduction method using bivariate Gaussian density function in the wavelet domain. In our method, the probability model for the interstate dependency in the wavelet domain is modeled by bivariate Gaussian function, and then, the noise reduction is performed by Bayesian estimation. The statistical parameter for Bayesian estimation can be approximately obtained by the $H{\ddot{o}}lder$ inequality. The simulation results show that our method outperforms the previous methods using bivariate probability models.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.6
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• pp.959-967
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• 1999

In this paper, we propose a Linear Prediction Method(LPM) in conjunction with signal enhancement for solving the direction-of-arrival estimation problem of multiple incoherent plane waves incident on a uniform linear array. The basic idea of signal enhancement is that of finding the covariance matrix of given rank that lies closest to a given estimated matrix in Frobenius norm sense. It is well known that LPM has a high-resolution performance in general applications, while it provides a lower statistical performance in lower SNR environment. To solve this problem, the LPM combined with signal enhancement approach is herein proposed. Simulation results are illustrated to demonstrate the better performance of the proposed method than conventional LPM.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.3
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• pp.173-181
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• 2019

To estimate probabilistic distribution function from experimental data, kernel density estimation(KDE) is mostly used in cases when data is insufficient. The estimated distribution using KDE depends on bandwidth selectors that smoothen or overfit a kernel estimator to experimental data. In this study, various bandwidth selectors such as the Silverman's rule of thumb, rule using adaptive estimates, and oversmoothing rule, were compared for accuracy and conservativeness. For this, statistical simulations were carried out using assumed true models including unimodal and multimodal distributions, and, accuracies and conservativeness of estimating distribution functions were compared according to various data. In addition, it was verified how the estimated distributions using KDE with different bandwidth selectors affect reliability analysis results through simple reliability examples.

• The Korean Journal of Applied Statistics
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• v.26 no.6
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• pp.1033-1041
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• 2013

In this paper, we investigate several variance estimators for pps systematic sampling. Unfortunately, there is no unbiased variance estimators for a systematic sample because systematic sampling can be regarded as a random selection of one cluster. This study provides guidance on which variance estimator may be more appropriate than others in several circumstances. We judge the efficiency of variance estimators for systematic sampling based on of their relative biases and relative mean square error. Also, we investigate variance estimation problems for two-stage systematic sampling applied for the Food Raw Material Consumption Survey and the Establishment Labor Force Survey simulation study, in order to consider the popular two-stage pps systematic sample design for establishment and household survey in Korea.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.103-115
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• 2007

In this paper we studied the small sample asymptotic inference for the autoregressive coefficient in AR(1) model. Based on saddlepoint approximations to the distribution of quadratic forms, we suggest a new approximation to the distribution of the estimators of the noncircular autoregressive coefficients. Simulation results show that the suggested methods are very accurate even in the small sample sizes and extreme tail area.

• The Transactions of the Korea Information Processing Society
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• v.6 no.9
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• pp.2343-2349
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• 1999

The hyper-geometric distribution software reliability growth model (HGDM) was recently developed and successfully applied to real data sets. The HGDM considers the sensitivity factor as a parameter to be estimated. In order to reflect the random behavior of the test-and-debug process, this paper generalizes the HGDM by assuming that the sensitivity factor is a binomial random variable. Such a generalization enables us to easily understand the statistical characteristics of the HGDM. It is shown that the least squares method produces the identical results for both the HGDM and the generalized HGDM. Methods for computing the maximum likelihood estimates and predicting the future outcomes are also presented.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1181-1190
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• 2010

When an insurer develops an insurance product, it is very critical to determine reasonable premiums, which is directly related to insurer's profits. There are three methods to determine premiums. Frist, the insurer utilizes premiums paid to the similar cases to the current one. Second, the insurer calculates premiums based on policyholder's past records. The last method is to combine the first with the second one. Based on the three methods, there are two major theories determining premiums, Limited Fluctuation Credibility Theory not based on statistical models and Greatest Accuracy Credibility Theory based on statistical models. There are well-known methods derived from Greatest Accuracy Credibility Theory, such as, Buhlmann model and Buhlmann-Straub model. In this paper, we extend the Buhlmann-Straub model to accommodate the fact that variability grows according to the number of data in practice and suggest a new non-parametric method to estimate the premiums. The suggested estimation method is also applied to the data gained from simulation and compared with the existing estimation method.